Motor control systems are widely used to control various aspects of motor performance in a broad spectrum of applications in which electric motors drive loads. Induction motors are asynchronous AC motors having a stator with stator windings providing a rotating AC stator field, with a rotor attached to the motor shaft to rotate within the stator field. Induction motors generally include a so-called squirrel cage rotor with the rotor rotating at a speed less than the rotational speed of the rotating stator field. The rotation of the stator magnetic field induces a current in the rotor conductors, in turn creating a rotor magnetic field that causes the rotor to turn in the direction the stator field is rotating. For many electric motor applications, control of the motor speed is important, particularly where the shaft load varies. In this regard, speed control during startup is particularly important in many motor control applications.
To regulate the motor performance according to a desired speed, it is necessary to measure or estimate the actual rotational speed of the rotor at any given time. In certain induction motor control architectures, moreover, soft-starters are used to energize the stator windings during startup, with the soft startup controls being bypassed once the motor reaches the normal operating speed, in order to minimize steady state heat generation. Many conventional motor control systems employ some form of tachometer or other sensor device mechanically coupled to the motor shaft to produce a feedback signal representing the motor speed, to facilitate closed loop startup speed control. However, such external sensors add cost to the motor drive system, and require maintenance.
Sensorless systems have been proposed and introduced, often employing model-based estimation or speed estimation based on measuring stator current harmonic content. However, actual motor startup times using these systems often varies with line voltage and motor load, which makes it difficult to coordinate motor startup with other equipment in various automated systems. Model-based approaches in particular suffer from variance in motor parameters and weak signals during motor startup. Stator-current-harmonics-based approaches require complex signal processing and the measured harmonics are related to the rotor structure, whereby the speed estimate cannot be updated quickly. Thus, there is a continuing need for improved motor controls and sensorless speed estimation techniques and systems for motor control applications, particularly for controlling motor speeds during startup.